Bangladesh / CCAFS / Climate Change / Geodata / ILRI / India / Pakistan / Report

Climate models need to shift focus from global to regional


(Picture on Flickr by Zoriah.)

A new report focusing on eastern and western Africa and the South Asian Indo-Gangetic Plains, which span parts of Bangladesh, India, Nepal and Pakistan, on the ability of global climate models to predict regional climate events such as monsoon rains and temperatures—and found mixed results.

‘The models have a reasonable capability in terms of reproducing [trends in the] East African climate,’ said Richard Washington, professor of climate science at the University of Oxford.

‘But in West Africa, particularly in the Sahel region, the models predicted more monsoon rains, of different duration, to those that were actually observed.

‘Similar difficulties were encountered with India’s monsoons, the authors said. . . .

‘The authors said global models often failed to take account of complex regional climatic factors—making them less useful for policymakers.

‘For example, Asia’s monsoons are affected by many region-specific factors, such as El Niño events, atmospheric pressure over the North Atlantic Ocean, and Asia’s so-called ‘brown cloud’ air pollution. . . .

‘The authors suggested greater use of ‘ensemble’ models which combine results from several models to generate averages; and also the use of global models in conjunction with regional ones, to enable regional information to be factored in alongside larger-scale processes. . . .’

‘Philip Thornton, a senior scientist at the International Livestock Research Institute in Kenya and a modelling tools leader at CCAFS told SciDev.Net:

The more we understand [uncertainty in models], the better we can deal with it.’

Read the whole article at SciDev.Net: Global climate models ‘need regional sensitivity, 13 Mar 2012.

Read more about the report, developed by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), on the ILRI News Blog: New reports explore reliability of climate models at predicting impacts on agriculture, 21 Feb 2012.

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